
Drug Discovery Today, Год журнала: 2024, Номер 30(1), С. 104255 - 104255
Опубликована: Ноя. 29, 2024
Язык: Английский
Drug Discovery Today, Год журнала: 2024, Номер 30(1), С. 104255 - 104255
Опубликована: Ноя. 29, 2024
Язык: Английский
Journal of Psychiatry and Neuroscience, Год журнала: 2025, Номер 50(1), С. E67 - E72
Опубликована: Фев. 7, 2025
> Consider the practical effects of objects your conception. Then, conception those is whole object. — Charles Sanders Peirce[1][1] Each us has an individual mental phenomenon that defines us. Some our differences and similarities
Язык: Английский
Процитировано
0Neuropsychopharmacology, Год журнала: 2024, Номер 50(1), С. 184 - 195
Опубликована: Авг. 28, 2024
Язык: Английский
Процитировано
2Frontiers in Psychiatry, Год журнала: 2024, Номер 15
Опубликована: Сен. 10, 2024
Prescription Digital Therapeutics (PDTs) are emerging as promising tools for treating and managing mental brain health conditions within the context of daily life. This commentary distinguishes PDTs from other Software Medical Devices (SaMD) explores their integration into treatments. We focus on research programs support National Institutes Health (NIH), discussing PDT supported by NIH's Institute Child Development (NICHD), Mental (NIMH), Aging (NIA). present a hierarchical natural language processing topic analysis NIH-funded digital therapeutics projects. delineate landscape across different disorders while highlighting opportunities challenges. Additionally, we discuss foundation PDTs, unique therapeutic approaches they employ, potential strategies to improve validity, reliability, safety, effectiveness. Finally, address collaborations necessary propel field forward, ultimately enhancing patient care through innovative solutions.
Язык: Английский
Процитировано
0medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown
Опубликована: Ноя. 15, 2024
New technologies for the quantification of behavior have revolutionized animal studies in social, cognitive, and pharmacological neurosciences. However, comparable understanding human behavior, especially psychiatry, are lacking. In this study, we utilized data-driven machine learning to analyze natural, spontaneous open-field behaviors from people with euthymic bipolar disorder (BD) non-BD participants. Our computational paradigm identified representations distinct sets actions (
Язык: Английский
Процитировано
0Drug Discovery Today, Год журнала: 2024, Номер 30(1), С. 104255 - 104255
Опубликована: Ноя. 29, 2024
Язык: Английский
Процитировано
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